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projector_test.cc
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projector_test.cc
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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
#ifndef M_PI
#define M_PI 3.14159265358979323846
#endif
#include "gandiva/projector.h"
#include <gtest/gtest.h>
#include <cmath>
#include "arrow/memory_pool.h"
#include "gandiva/literal_holder.h"
#include "gandiva/node.h"
#include "gandiva/tests/test_util.h"
#include "gandiva/tree_expr_builder.h"
namespace gandiva {
using arrow::boolean;
using arrow::float32;
using arrow::int32;
using arrow::int64;
class TestProjector : public ::testing::Test {
public:
void SetUp() {
pool_ = arrow::default_memory_pool();
// Setup arrow log severity threshold to debug level.
arrow::util::ArrowLog::StartArrowLog("", arrow::util::ArrowLogLevel::ARROW_DEBUG);
}
protected:
arrow::MemoryPool* pool_;
};
TEST_F(TestProjector, TestProjectCache) {
// schema for input fields
auto field0 = field("f0", int32());
auto field1 = field("f2", int32());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_sum = field("add", int32());
auto field_sub = field("subtract", int32());
// Build expression
auto sum_expr = TreeExprBuilder::MakeExpression("add", {field0, field1}, field_sum);
auto sub_expr =
TreeExprBuilder::MakeExpression("subtract", {field0, field1}, field_sub);
auto configuration = TestConfiguration();
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {sum_expr, sub_expr}, configuration, &projector);
ASSERT_OK(status);
EXPECT_FALSE(projector->GetBuiltFromCache());
// everything is same, should return the same projector.
auto schema_same = arrow::schema({field0, field1});
std::shared_ptr<Projector> cached_projector;
status = Projector::Make(schema_same, {sum_expr, sub_expr}, configuration,
&cached_projector);
ASSERT_OK(status);
EXPECT_TRUE(cached_projector->GetBuiltFromCache());
// schema is different should return a new projector.
auto field2 = field("f2", int32());
auto different_schema = arrow::schema({field0, field1, field2});
std::shared_ptr<Projector> should_be_new_projector;
status = Projector::Make(different_schema, {sum_expr, sub_expr}, configuration,
&should_be_new_projector);
ASSERT_OK(status);
EXPECT_FALSE(should_be_new_projector->GetBuiltFromCache());
// expression list is different should return a new projector.
std::shared_ptr<Projector> should_be_new_projector1;
status = Projector::Make(schema, {sum_expr}, configuration, &should_be_new_projector1);
ASSERT_OK(status);
EXPECT_FALSE(should_be_new_projector1->GetBuiltFromCache());
// another instance of the same configuration, should return the same projector.
status = Projector::Make(schema, {sum_expr, sub_expr}, TestConfiguration(),
&cached_projector);
ASSERT_OK(status);
EXPECT_TRUE(cached_projector->GetBuiltFromCache());
}
TEST_F(TestProjector, TestProjectCacheFieldNames) {
// schema for input fields
auto field0 = field("f0", int32());
auto field1 = field("f1", int32());
auto field2 = field("f2", int32());
auto schema = arrow::schema({field0, field1, field2});
// output fields
auto sum_01 = field("sum_01", int32());
auto sum_12 = field("sum_12", int32());
auto sum_expr_01 = TreeExprBuilder::MakeExpression("add", {field0, field1}, sum_01);
std::shared_ptr<Projector> projector_01;
auto status =
Projector::Make(schema, {sum_expr_01}, TestConfiguration(), &projector_01);
EXPECT_TRUE(status.ok());
auto sum_expr_12 = TreeExprBuilder::MakeExpression("add", {field1, field2}, sum_12);
std::shared_ptr<Projector> projector_12;
status = Projector::Make(schema, {sum_expr_12}, TestConfiguration(), &projector_12);
EXPECT_TRUE(status.ok());
// add(f0, f1) != add(f1, f2)
EXPECT_TRUE(projector_01.get() != projector_12.get());
}
TEST_F(TestProjector, TestProjectCacheDouble) {
auto schema = arrow::schema({});
auto res = field("result", arrow::float64());
double d0 = 1.23456788912345677E18;
double d1 = 1.23456789012345677E18;
auto literal0 = TreeExprBuilder::MakeLiteral(d0);
auto expr0 = TreeExprBuilder::MakeExpression(literal0, res);
auto configuration = TestConfiguration();
std::shared_ptr<Projector> projector0;
auto status = Projector::Make(schema, {expr0}, configuration, &projector0);
EXPECT_TRUE(status.ok()) << status.message();
auto literal1 = TreeExprBuilder::MakeLiteral(d1);
auto expr1 = TreeExprBuilder::MakeExpression(literal1, res);
std::shared_ptr<Projector> projector1;
status = Projector::Make(schema, {expr1}, configuration, &projector1);
EXPECT_TRUE(status.ok()) << status.message();
EXPECT_TRUE(projector0.get() != projector1.get());
}
TEST_F(TestProjector, TestProjectCacheFloat) {
auto schema = arrow::schema({});
auto res = field("result", arrow::float32());
float f0 = static_cast<float>(12345678891.000000);
float f1 = f0 - 1000;
auto literal0 = TreeExprBuilder::MakeLiteral(f0);
auto expr0 = TreeExprBuilder::MakeExpression(literal0, res);
std::shared_ptr<Projector> projector0;
auto status = Projector::Make(schema, {expr0}, TestConfiguration(), &projector0);
EXPECT_TRUE(status.ok()) << status.message();
auto literal1 = TreeExprBuilder::MakeLiteral(f1);
auto expr1 = TreeExprBuilder::MakeExpression(literal1, res);
std::shared_ptr<Projector> projector1;
status = Projector::Make(schema, {expr1}, TestConfiguration(), &projector1);
EXPECT_TRUE(status.ok()) << status.message();
EXPECT_TRUE(projector0.get() != projector1.get());
}
TEST_F(TestProjector, TestProjectCacheLiteral) {
auto schema = arrow::schema({});
auto res = field("result", arrow::decimal(38, 5));
DecimalScalar128 d0("12345678", 38, 5);
DecimalScalar128 d1("98756432", 38, 5);
auto literal0 = TreeExprBuilder::MakeDecimalLiteral(d0);
auto expr0 = TreeExprBuilder::MakeExpression(literal0, res);
std::shared_ptr<Projector> projector0;
ASSERT_OK(Projector::Make(schema, {expr0}, TestConfiguration(), &projector0));
auto literal1 = TreeExprBuilder::MakeDecimalLiteral(d1);
auto expr1 = TreeExprBuilder::MakeExpression(literal1, res);
std::shared_ptr<Projector> projector1;
ASSERT_OK(Projector::Make(schema, {expr1}, TestConfiguration(), &projector1));
EXPECT_NE(projector0.get(), projector1.get());
}
TEST_F(TestProjector, TestProjectCacheDecimalCast) {
auto field_float64 = field("float64", arrow::float64());
auto schema = arrow::schema({field_float64});
auto res_31_13 = field("result", arrow::decimal(31, 13));
auto expr0 = TreeExprBuilder::MakeExpression("castDECIMAL", {field_float64}, res_31_13);
std::shared_ptr<Projector> projector0;
ASSERT_OK(Projector::Make(schema, {expr0}, TestConfiguration(), &projector0));
EXPECT_FALSE(projector0->GetBuiltFromCache());
// if the output scale is different, the cache can't be used.
auto res_31_14 = field("result", arrow::decimal(31, 14));
auto expr1 = TreeExprBuilder::MakeExpression("castDECIMAL", {field_float64}, res_31_14);
std::shared_ptr<Projector> projector1;
ASSERT_OK(Projector::Make(schema, {expr1}, TestConfiguration(), &projector1));
EXPECT_FALSE(projector1->GetBuiltFromCache());
// if the output scale/precision are same, should get a cache hit.
auto res_31_13_alt = field("result", arrow::decimal(31, 13));
auto expr2 =
TreeExprBuilder::MakeExpression("castDECIMAL", {field_float64}, res_31_13_alt);
std::shared_ptr<Projector> projector2;
ASSERT_OK(Projector::Make(schema, {expr2}, TestConfiguration(), &projector2));
EXPECT_TRUE(projector2->GetBuiltFromCache());
}
TEST_F(TestProjector, TestFactorial) {
// schema for input fields
auto field0 = field("f0", arrow::int64());
auto schema = arrow::schema({field0});
// output fields
auto field_fac = field("fact", arrow::int64());
// Build expression
auto fac_expr = TreeExprBuilder::MakeExpression("factorial", {field0}, field_fac);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {fac_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt64({1, 2, 3, 4}, {true, true, true, true});
// expected output
auto exp_fac = MakeArrowArrayInt64({1, 2, 6, 24}, {true, true, true, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_fac, outputs.at(0));
}
TEST_F(TestProjector, TestIntSumSub) {
// schema for input fields
auto field0 = field("f0", int32());
auto field1 = field("f2", int32());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_sum = field("add", int32());
auto field_sub = field("subtract", int32());
// Build expression
auto sum_expr = TreeExprBuilder::MakeExpression("add", {field0, field1}, field_sum);
auto sub_expr =
TreeExprBuilder::MakeExpression("subtract", {field0, field1}, field_sub);
std::shared_ptr<Projector> projector;
auto status =
Projector::Make(schema, {sum_expr, sub_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt32({1, 2, 3, 4}, {true, true, true, false});
auto array1 = MakeArrowArrayInt32({11, 13, 15, 17}, {true, true, false, true});
// expected output
auto exp_sum = MakeArrowArrayInt32({12, 15, 0, 0}, {true, true, false, false});
auto exp_sub = MakeArrowArrayInt32({-10, -11, 0, 0}, {true, true, false, false});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_sum, outputs.at(0));
EXPECT_ARROW_ARRAY_EQUALS(exp_sub, outputs.at(1));
}
template <typename TYPE, typename C_TYPE>
static void TestArithmeticOpsForType(arrow::MemoryPool* pool) {
auto atype = arrow::TypeTraits<TYPE>::type_singleton();
// schema for input fields
auto field0 = field("f0", atype);
auto field1 = field("f1", atype);
auto schema = arrow::schema({field0, field1});
// output fields
auto field_sum = field("add", atype);
auto field_sub = field("subtract", atype);
auto field_mul = field("multiply", atype);
auto field_div = field("divide", atype);
auto field_eq = field("equal", arrow::boolean());
auto field_lt = field("less_than", arrow::boolean());
// Build expression
auto sum_expr = TreeExprBuilder::MakeExpression("add", {field0, field1}, field_sum);
auto sub_expr =
TreeExprBuilder::MakeExpression("subtract", {field0, field1}, field_sub);
auto mul_expr =
TreeExprBuilder::MakeExpression("multiply", {field0, field1}, field_mul);
auto div_expr = TreeExprBuilder::MakeExpression("divide", {field0, field1}, field_div);
auto eq_expr = TreeExprBuilder::MakeExpression("equal", {field0, field1}, field_eq);
auto lt_expr = TreeExprBuilder::MakeExpression("less_than", {field0, field1}, field_lt);
std::shared_ptr<Projector> projector;
auto status =
Projector::Make(schema, {sum_expr, sub_expr, mul_expr, div_expr, eq_expr, lt_expr},
TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 12;
std::vector<C_TYPE> input0 = {1, 2, 53, 84, 5, 15, 0, 1, 52, 83, 4, 120};
std::vector<C_TYPE> input1 = {10, 15, 23, 84, 4, 51, 68, 9, 16, 18, 19, 37};
std::vector<bool> validity = {true, true, true, true, true, true,
true, true, true, true, true, true};
auto array0 = MakeArrowArray<TYPE, C_TYPE>(input0, validity);
auto array1 = MakeArrowArray<TYPE, C_TYPE>(input1, validity);
// expected output
std::vector<C_TYPE> sum;
std::vector<C_TYPE> sub;
std::vector<C_TYPE> mul;
std::vector<C_TYPE> div;
std::vector<bool> eq;
std::vector<bool> lt;
for (int i = 0; i < num_records; i++) {
sum.push_back(static_cast<C_TYPE>(input0[i] + input1[i]));
sub.push_back(static_cast<C_TYPE>(input0[i] - input1[i]));
mul.push_back(static_cast<C_TYPE>(input0[i] * input1[i]));
div.push_back(static_cast<C_TYPE>(input0[i] / input1[i]));
eq.push_back(input0[i] == input1[i]);
lt.push_back(input0[i] < input1[i]);
}
auto exp_sum = MakeArrowArray<TYPE, C_TYPE>(sum, validity);
auto exp_sub = MakeArrowArray<TYPE, C_TYPE>(sub, validity);
auto exp_mul = MakeArrowArray<TYPE, C_TYPE>(mul, validity);
auto exp_div = MakeArrowArray<TYPE, C_TYPE>(div, validity);
auto exp_eq = MakeArrowArray<arrow::BooleanType, bool>(eq, validity);
auto exp_lt = MakeArrowArray<arrow::BooleanType, bool>(lt, validity);
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_sum, outputs.at(0));
EXPECT_ARROW_ARRAY_EQUALS(exp_sub, outputs.at(1));
EXPECT_ARROW_ARRAY_EQUALS(exp_mul, outputs.at(2));
EXPECT_ARROW_ARRAY_EQUALS(exp_div, outputs.at(3));
EXPECT_ARROW_ARRAY_EQUALS(exp_eq, outputs.at(4));
EXPECT_ARROW_ARRAY_EQUALS(exp_lt, outputs.at(5));
}
TEST_F(TestProjector, TestAllIntTypes) {
TestArithmeticOpsForType<arrow::UInt8Type, uint8_t>(pool_);
TestArithmeticOpsForType<arrow::UInt16Type, uint16_t>(pool_);
TestArithmeticOpsForType<arrow::UInt32Type, uint32_t>(pool_);
TestArithmeticOpsForType<arrow::UInt64Type, uint64_t>(pool_);
TestArithmeticOpsForType<arrow::Int8Type, int8_t>(pool_);
TestArithmeticOpsForType<arrow::Int16Type, int16_t>(pool_);
TestArithmeticOpsForType<arrow::Int32Type, int32_t>(pool_);
TestArithmeticOpsForType<arrow::Int64Type, int64_t>(pool_);
}
TEST_F(TestProjector, TestExtendedMath) {
// schema for input fields
auto field0 = arrow::field("f0", arrow::float64());
auto field1 = arrow::field("f1", arrow::float64());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_cbrt = arrow::field("cbrt", arrow::float64());
auto field_exp = arrow::field("exp", arrow::float64());
auto field_log = arrow::field("log", arrow::float64());
auto field_log10 = arrow::field("log10", arrow::float64());
auto field_logb = arrow::field("logb", arrow::float64());
auto field_power = arrow::field("power", arrow::float64());
auto field_sin = arrow::field("sin", arrow::float64());
auto field_cos = arrow::field("cos", arrow::float64());
auto field_asin = arrow::field("asin", arrow::float64());
auto field_acos = arrow::field("acos", arrow::float64());
auto field_tan = arrow::field("tan", arrow::float64());
auto field_atan = arrow::field("atan", arrow::float64());
auto field_sinh = arrow::field("sinh", arrow::float64());
auto field_cosh = arrow::field("cosh", arrow::float64());
auto field_tanh = arrow::field("tanh", arrow::float64());
auto field_atan2 = arrow::field("atan2", arrow::float64());
auto field_cot = arrow::field("cot", arrow::float64());
auto field_radians = arrow::field("radians", arrow::float64());
auto field_degrees = arrow::field("degrees", arrow::float64());
auto field_udfdegrees = arrow::field("udfdegrees", arrow::float64());
// Build expression
auto cbrt_expr = TreeExprBuilder::MakeExpression("cbrt", {field0}, field_cbrt);
auto exp_expr = TreeExprBuilder::MakeExpression("exp", {field0}, field_exp);
auto log_expr = TreeExprBuilder::MakeExpression("log", {field0}, field_log);
auto log10_expr = TreeExprBuilder::MakeExpression("log10", {field0}, field_log10);
auto logb_expr = TreeExprBuilder::MakeExpression("log", {field0, field1}, field_logb);
auto power_expr =
TreeExprBuilder::MakeExpression("power", {field0, field1}, field_power);
auto sin_expr = TreeExprBuilder::MakeExpression("sin", {field0}, field_sin);
auto cos_expr = TreeExprBuilder::MakeExpression("cos", {field0}, field_cos);
auto asin_expr = TreeExprBuilder::MakeExpression("asin", {field0}, field_asin);
auto acos_expr = TreeExprBuilder::MakeExpression("acos", {field0}, field_acos);
auto tan_expr = TreeExprBuilder::MakeExpression("tan", {field0}, field_tan);
auto atan_expr = TreeExprBuilder::MakeExpression("atan", {field0}, field_atan);
auto sinh_expr = TreeExprBuilder::MakeExpression("sinh", {field0}, field_sinh);
auto cosh_expr = TreeExprBuilder::MakeExpression("cosh", {field0}, field_cosh);
auto tanh_expr = TreeExprBuilder::MakeExpression("tanh", {field0}, field_tanh);
auto atan2_expr =
TreeExprBuilder::MakeExpression("atan2", {field0, field1}, field_atan2);
auto cot_expr = TreeExprBuilder::MakeExpression("cot", {field0}, field_cot);
auto radians_expr = TreeExprBuilder::MakeExpression("radians", {field0}, field_radians);
auto degrees_expr = TreeExprBuilder::MakeExpression("degrees", {field0}, field_degrees);
auto udfdegrees_expr =
TreeExprBuilder::MakeExpression("udfdegrees", {field0}, field_udfdegrees);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(
schema, {cbrt_expr, exp_expr, log_expr, log10_expr, logb_expr,
power_expr, sin_expr, cos_expr, asin_expr, acos_expr,
tan_expr, atan_expr, sinh_expr, cosh_expr, tanh_expr,
atan2_expr, cot_expr, radians_expr, degrees_expr, udfdegrees_expr},
TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 4;
std::vector<double> input0 = {16, 10, -14, 8.3};
std::vector<double> input1 = {2, 3, 5, 7};
std::vector<bool> validity = {true, true, true, true};
auto array0 = MakeArrowArray<arrow::DoubleType, double>(input0, validity);
auto array1 = MakeArrowArray<arrow::DoubleType, double>(input1, validity);
// expected output
std::vector<double> cbrt_vals;
std::vector<double> exp_vals;
std::vector<double> log_vals;
std::vector<double> log10_vals;
std::vector<double> logb_vals;
std::vector<double> power_vals;
std::vector<double> sin_vals;
std::vector<double> cos_vals;
std::vector<double> asin_vals;
std::vector<double> acos_vals;
std::vector<double> tan_vals;
std::vector<double> atan_vals;
std::vector<double> sinh_vals;
std::vector<double> cosh_vals;
std::vector<double> tanh_vals;
std::vector<double> atan2_vals;
std::vector<double> cot_vals;
std::vector<double> radians_vals;
std::vector<double> degrees_vals;
std::vector<double> udfdegrees_vals;
for (int i = 0; i < num_records; i++) {
cbrt_vals.push_back(static_cast<double>(cbrtl(input0[i])));
exp_vals.push_back(static_cast<double>(expl(input0[i])));
log_vals.push_back(static_cast<double>(logl(input0[i])));
log10_vals.push_back(static_cast<double>(log10l(input0[i])));
logb_vals.push_back(static_cast<double>(logl(input1[i]) / logl(input0[i])));
power_vals.push_back(static_cast<double>(powl(input0[i], input1[i])));
sin_vals.push_back(static_cast<double>(sin(input0[i])));
cos_vals.push_back(static_cast<double>(cos(input0[i])));
asin_vals.push_back(static_cast<double>(asin(input0[i])));
acos_vals.push_back(static_cast<double>(acos(input0[i])));
tan_vals.push_back(static_cast<double>(tan(input0[i])));
atan_vals.push_back(static_cast<double>(atan(input0[i])));
sinh_vals.push_back(static_cast<double>(sinh(input0[i])));
cosh_vals.push_back(static_cast<double>(cosh(input0[i])));
tanh_vals.push_back(static_cast<double>(tanh(input0[i])));
atan2_vals.push_back(static_cast<double>(atan2(input0[i], input1[i])));
cot_vals.push_back(static_cast<double>(tan(M_PI / 2 - input0[i])));
radians_vals.push_back(static_cast<double>(input0[i] * M_PI / 180.0));
degrees_vals.push_back(static_cast<double>(input0[i] * 180.0 / M_PI));
udfdegrees_vals.push_back(static_cast<double>(input0[i] * 180.0 / M_PI));
}
auto expected_cbrt = MakeArrowArray<arrow::DoubleType, double>(cbrt_vals, validity);
auto expected_exp = MakeArrowArray<arrow::DoubleType, double>(exp_vals, validity);
auto expected_log = MakeArrowArray<arrow::DoubleType, double>(log_vals, validity);
auto expected_log10 = MakeArrowArray<arrow::DoubleType, double>(log10_vals, validity);
auto expected_logb = MakeArrowArray<arrow::DoubleType, double>(logb_vals, validity);
auto expected_power = MakeArrowArray<arrow::DoubleType, double>(power_vals, validity);
auto expected_sin = MakeArrowArray<arrow::DoubleType, double>(sin_vals, validity);
auto expected_cos = MakeArrowArray<arrow::DoubleType, double>(cos_vals, validity);
auto expected_asin = MakeArrowArray<arrow::DoubleType, double>(asin_vals, validity);
auto expected_acos = MakeArrowArray<arrow::DoubleType, double>(acos_vals, validity);
auto expected_tan = MakeArrowArray<arrow::DoubleType, double>(tan_vals, validity);
auto expected_atan = MakeArrowArray<arrow::DoubleType, double>(atan_vals, validity);
auto expected_sinh = MakeArrowArray<arrow::DoubleType, double>(sinh_vals, validity);
auto expected_cosh = MakeArrowArray<arrow::DoubleType, double>(cosh_vals, validity);
auto expected_tanh = MakeArrowArray<arrow::DoubleType, double>(tanh_vals, validity);
auto expected_atan2 = MakeArrowArray<arrow::DoubleType, double>(atan2_vals, validity);
auto expected_cot = MakeArrowArray<arrow::DoubleType, double>(cot_vals, validity);
auto expected_radians =
MakeArrowArray<arrow::DoubleType, double>(radians_vals, validity);
auto expected_degrees =
MakeArrowArray<arrow::DoubleType, double>(degrees_vals, validity);
auto expected_udfdegrees =
MakeArrowArray<arrow::DoubleType, double>(udfdegrees_vals, validity);
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
double epsilon = 1E-13;
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_cbrt, outputs.at(0), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_exp, outputs.at(1), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_log, outputs.at(2), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_log10, outputs.at(3), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_logb, outputs.at(4), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_power, outputs.at(5), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_sin, outputs.at(6), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_cos, outputs.at(7), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_asin, outputs.at(8), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_acos, outputs.at(9), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_tan, outputs.at(10), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_atan, outputs.at(11), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_sinh, outputs.at(12), 1E-08);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_cosh, outputs.at(13), 1E-08);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_tanh, outputs.at(14), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_atan2, outputs.at(15), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_cot, outputs.at(16), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_radians, outputs.at(17), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_degrees, outputs.at(18), epsilon);
EXPECT_ARROW_ARRAY_APPROX_EQUALS(expected_udfdegrees, outputs.at(19), epsilon);
}
TEST_F(TestProjector, TestFloatLessThan) {
// schema for input fields
auto field0 = field("f0", float32());
auto field1 = field("f2", float32());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_result = field("res", boolean());
// Build expression
auto lt_expr =
TreeExprBuilder::MakeExpression("less_than", {field0, field1}, field_result);
// Build a projector for the expressions.
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {lt_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 3;
auto array0 = MakeArrowArrayFloat32({1.0f, 8.9f, 3.0f}, {true, true, false});
auto array1 = MakeArrowArrayFloat32({4.0f, 3.4f, 6.8f}, {true, true, true});
// expected output
auto exp = MakeArrowArrayBool({true, false, false}, {true, true, false});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp, outputs.at(0));
}
TEST_F(TestProjector, TestIsNotNull) {
// schema for input fields
auto field0 = field("f0", float32());
auto schema = arrow::schema({field0});
// output fields
auto field_result = field("res", boolean());
// Build expression
auto myexpr = TreeExprBuilder::MakeExpression("isnotnull", {field0}, field_result);
// Build a projector for the expressions.
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {myexpr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 3;
auto array0 = MakeArrowArrayFloat32({1.0f, 8.9f, 3.0f}, {true, true, false});
// expected output
auto exp = MakeArrowArrayBool({true, true, false}, {true, true, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp, outputs.at(0));
}
TEST_F(TestProjector, TestZeroCopy) {
// schema for input fields
auto field0 = field("f0", int32());
auto schema = arrow::schema({field0});
// output fields
auto res = field("res", float32());
// Build expression
auto cast_expr = TreeExprBuilder::MakeExpression("castFLOAT4", {field0}, res);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {cast_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt32({1, 2, 3, 4}, {true, true, true, false});
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0});
// expected output
auto exp = MakeArrowArrayFloat32({1, 2, 3, 0}, {true, true, true, false});
// allocate output buffers
int64_t bitmap_sz = arrow::bit_util::BytesForBits(num_records);
int64_t bitmap_capacity = arrow::bit_util::RoundUpToMultipleOf64(bitmap_sz);
std::vector<uint8_t> bitmap(bitmap_capacity);
std::shared_ptr<arrow::MutableBuffer> bitmap_buf =
std::make_shared<arrow::MutableBuffer>(&bitmap[0], bitmap_capacity);
int64_t data_sz = sizeof(float) * num_records;
std::vector<uint8_t> data(bitmap_capacity);
std::shared_ptr<arrow::MutableBuffer> data_buf =
std::make_shared<arrow::MutableBuffer>(&data[0], data_sz);
auto array_data =
arrow::ArrayData::Make(float32(), num_records, {bitmap_buf, data_buf});
// Evaluate expression
status = projector->Evaluate(*in_batch, {array_data});
EXPECT_TRUE(status.ok());
// Validate results
auto output = arrow::MakeArray(array_data);
EXPECT_ARROW_ARRAY_EQUALS(exp, output);
}
TEST_F(TestProjector, TestZeroCopyNegative) {
// schema for input fields
auto field0 = field("f0", int32());
auto schema = arrow::schema({field0});
// output fields
auto res = field("res", float32());
// Build expression
auto cast_expr = TreeExprBuilder::MakeExpression("castFLOAT4", {field0}, res);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {cast_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok());
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt32({1, 2, 3, 4}, {true, true, true, false});
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0});
// expected output
auto exp = MakeArrowArrayFloat32({1, 2, 3, 0}, {true, true, true, false});
// allocate output buffers
int64_t bitmap_sz = arrow::bit_util::BytesForBits(num_records);
std::unique_ptr<uint8_t[]> bitmap(new uint8_t[bitmap_sz]);
std::shared_ptr<arrow::MutableBuffer> bitmap_buf =
std::make_shared<arrow::MutableBuffer>(bitmap.get(), bitmap_sz);
int64_t data_sz = sizeof(float) * num_records;
std::unique_ptr<uint8_t[]> data(new uint8_t[data_sz]);
std::shared_ptr<arrow::MutableBuffer> data_buf =
std::make_shared<arrow::MutableBuffer>(data.get(), data_sz);
auto array_data =
arrow::ArrayData::Make(float32(), num_records, {bitmap_buf, data_buf});
// the batch can't be empty.
auto bad_batch = arrow::RecordBatch::Make(schema, 0 /*num_records*/, {array0});
status = projector->Evaluate(*bad_batch, {array_data});
EXPECT_EQ(status.code(), StatusCode::Invalid);
// the output array can't be null.
std::shared_ptr<arrow::ArrayData> null_array_data;
status = projector->Evaluate(*in_batch, {null_array_data});
EXPECT_EQ(status.code(), StatusCode::Invalid);
// the output array must have at least two buffers.
auto bad_array_data = arrow::ArrayData::Make(float32(), num_records, {bitmap_buf});
status = projector->Evaluate(*in_batch, {bad_array_data});
EXPECT_EQ(status.code(), StatusCode::Invalid);
// the output buffers must have sufficiently sized data_buf.
std::shared_ptr<arrow::MutableBuffer> bad_data_buf =
std::make_shared<arrow::MutableBuffer>(data.get(), data_sz - 1);
auto bad_array_data2 =
arrow::ArrayData::Make(float32(), num_records, {bitmap_buf, bad_data_buf});
status = projector->Evaluate(*in_batch, {bad_array_data2});
EXPECT_EQ(status.code(), StatusCode::Invalid);
// the output buffers must have sufficiently sized bitmap_buf.
std::shared_ptr<arrow::MutableBuffer> bad_bitmap_buf =
std::make_shared<arrow::MutableBuffer>(bitmap.get(), bitmap_sz - 1);
auto bad_array_data3 =
arrow::ArrayData::Make(float32(), num_records, {bad_bitmap_buf, data_buf});
status = projector->Evaluate(*in_batch, {bad_array_data3});
EXPECT_EQ(status.code(), StatusCode::Invalid);
}
TEST_F(TestProjector, TestDivideZero) {
// schema for input fields
auto field0 = field("f0", int32());
auto field1 = field("f2", int32());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_div = field("divide", int32());
// Build expression
auto div_expr = TreeExprBuilder::MakeExpression("divide", {field0, field1}, field_div);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {div_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Create a row-batch with some sample data
int num_records = 5;
auto array0 = MakeArrowArrayInt32({2, 3, 4, 5, 6}, {true, true, true, true, true});
auto array1 = MakeArrowArrayInt32({1, 2, 2, 0, 0}, {true, true, false, true, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_EQ(status.code(), StatusCode::ExecutionError);
std::string expected_error = "divide by zero error";
EXPECT_TRUE(status.message().find(expected_error) != std::string::npos);
// Testing for second batch that has no error should succeed.
num_records = 5;
array0 = MakeArrowArrayInt32({2, 3, 4, 5, 6}, {true, true, true, true, true});
array1 = MakeArrowArrayInt32({1, 2, 2, 1, 1}, {true, true, false, true, true});
// prepare input record batch
in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// expected output
auto exp = MakeArrowArrayInt32({2, 1, 2, 5, 6}, {true, true, false, true, true});
// Evaluate expression
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok());
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp, outputs.at(0));
}
TEST_F(TestProjector, TestXor) {
// schema for input fields
auto field0 = field("f0", int32());
auto field1 = field("f1", int32());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_xor = field("xor", int32());
// Build expression
auto mod_expr = TreeExprBuilder::MakeExpression("xor", {field0, field1}, field_xor);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {mod_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt32({2, 3, 1, 20}, {true, true, true, true});
auto array1 = MakeArrowArrayInt32({4, 1, 3, 0}, {true, true, true, true});
// expected output
auto exp_mod = MakeArrowArrayInt32({6, 2, 2, 20}, {true, true, true, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok()) << status.message();
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_mod, outputs.at(0));
}
TEST_F(TestProjector, TestSoundex) {
// schema for input fields
auto field0 = field("f0", arrow::utf8());
auto schema = arrow::schema({field0});
// output fields
auto field_base = field("soundex", arrow::utf8());
// Build expression
auto soundex_expr = TreeExprBuilder::MakeExpression("soundex", {field0}, field_base);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {soundex_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Create a row-batch with some sample data
int num_records = 11;
auto array0 = MakeArrowArrayUtf8(
{"test", "", "Miller", "abc", "democrat", "luke garcia", "alice ichabod", "Jjjice",
"SACHS", "路-大学b路%$大", "a"},
{true, true, true, true, true, true, true, true, true, true, true});
// expected output
auto exp_soundex = MakeArrowArrayUtf8(
{"T230", "", "M460", "A120", "D526", "L226", "A422", "J200", "S220", "B000",
"A000"},
{true, true, true, true, true, true, true, true, true, true, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok()) << status.message();
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_soundex, outputs.at(0));
}
TEST_F(TestProjector, TestModZero) {
// schema for input fields
auto field0 = field("f0", arrow::int64());
auto field1 = field("f2", int32());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_div = field("mod", int32());
// Build expression
auto mod_expr = TreeExprBuilder::MakeExpression("mod", {field0, field1}, field_div);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {mod_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt64({2, 3, 4, 5}, {true, true, true, true});
auto array1 = MakeArrowArrayInt32({1, 2, 2, 0}, {true, true, false, true});
// expected output
auto exp_mod = MakeArrowArrayInt32({0, 1, 0, 5}, {true, true, false, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok()) << status.message();
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_mod, outputs.at(0));
}
TEST_F(TestProjector, TestPmod) {
// schema for input fields
auto field0 = field("f0", arrow::int64());
auto field1 = field("f1", arrow::int64());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_pmod = field("pmod", arrow::int64());
// Build expression
auto pmod_expr = TreeExprBuilder::MakeExpression("pmod", {field0, field1}, field_pmod);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {pmod_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Create a row-batch with some sample data
int num_records = 4;
auto array0 = MakeArrowArrayInt64({3, 4, -3, -4}, {true, true, true, true});
auto array1 = MakeArrowArrayInt64({4, 3, 4, 3}, {true, true, true, true});
// expected output
auto exp_pmod = MakeArrowArrayInt64({3, 1, 1, 2}, {true, true, true, true});
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {array0, array1});
// Evaluate expression
arrow::ArrayVector outputs;
status = projector->Evaluate(*in_batch, pool_, &outputs);
EXPECT_TRUE(status.ok()) << status.message();
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_pmod, outputs.at(0));
}
TEST_F(TestProjector, TestGreatestLeast) {
// schema for input fields
auto f0 = field("f0", int32());
auto f1 = field("f1", int32());
auto f2 = field("f2", int32());
auto schema = arrow::schema({f0, f1, f2});
// output fields
auto field_greatest = field("greatest", int32());
auto field_least = field("least", int32());
// Build expression
auto greatest_expr =
TreeExprBuilder::MakeExpression("greatest", {f0, f1, f2}, field_greatest);
std::shared_ptr<Projector> projector;
auto status = Projector::Make(schema, {greatest_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Create a row-batch with some sample data
int num_records = 4;
auto a0 = MakeArrowArrayInt32({10, 20, 30, 40}, {true, true, true, true});
auto a1 = MakeArrowArrayInt32({2, 8, 50, 25}, {true, true, true, true});
auto a2 = MakeArrowArrayInt32({526, 32, 9, -5}, {true, true, true, true});
// expected output
auto exp_greatest = MakeArrowArrayInt32({526, 32, 50, 40}, {true, true, true, true});
auto exp_least = MakeArrowArrayInt32({2, 8, 9, -5}, {true, true, true, true});
// GREATEST
// prepare input record batch
auto in_batch = arrow::RecordBatch::Make(schema, num_records, {a0, a1, a2});
// Evaluate expression
arrow::ArrayVector outputs_grt;
status = projector->Evaluate(*in_batch, pool_, &outputs_grt);
EXPECT_TRUE(status.ok()) << status.message();
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_greatest, outputs_grt.at(0));
// LEAST
// Reproduce the same test now for the least operator
auto least_expr = TreeExprBuilder::MakeExpression("least", {f0, f1, f2}, field_least);
status = Projector::Make(schema, {least_expr}, TestConfiguration(), &projector);
EXPECT_TRUE(status.ok()) << status.message();
// Evaluate expression
arrow::ArrayVector outputs_lst;
status = projector->Evaluate(*in_batch, pool_, &outputs_lst);
EXPECT_TRUE(status.ok()) << status.message();
// Validate results
EXPECT_ARROW_ARRAY_EQUALS(exp_least, outputs_lst.at(0));
}
TEST_F(TestProjector, TestPositiveNegative) {
// schema for input fields
auto field0 = field("f0", int32());
auto field1 = field("f1", int64());
auto schema = arrow::schema({field0, field1});
// output fields
auto field_pos = field("positive", int32());